Advancements in the field of medical imaging have paved way to automate and provide real time assistance in surgical processes that are often complex and performed manually by surgeons. In one such process, during surgery, an internal organ, such as the brain of a subject may suffer an inevitable deformation that may be caused by initial brain shift due to expulsion of brain fluid, followed by, for example, a resection deformation. One of the primary causes of deformation is the intraoperative brain shift that is caused by tissue deformation that happens while the surgeon tries to operate on a target brain tissue in an exposed region of the brain. The effect of deformation on the exposed region of the brain causes difficulty in localization of the target brain tissue during the surgery with respect to pre-determined tissue positions obtained prior to the surgery (i.e. during pre-operative imaging). During surgery, such deformation may therefore lead a surgeon to a tissue that is different from a target tissue or may lead to inaccurate assumptions in positioning of the target tissue among different surgeons.
In medical practice, surgeons usually compensate for deformation of brain tissue based on their prior experience with similar surgical procedures. However, a mere assumption while compensating for deformation based on prior experience may affect accuracy and precision of the surgical procedure. Also, the precision with which the surgical procedure may be performed greatly depends on the experience level of the surgeon and therefore, an improved solution is required that may assist a surgeon in estimating precise intraoperative brain shift caused by tissue deformation during surgery.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one skilled in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.